Introduction to Central Limit Theorem in Statistics

Welcome to the session on 'Central Limit Theorem'. In the last session, you learnt about probability density functions, specifically normal and standard normal distributions.

In this session

You will learn what a sample is and why it is so error-prone. You will then understand how to quantify this error made in sampling using a popular theorem in statistics, called the central limit theorem.

Prerequisites

There are no prerequisites for this session, other than, of course, your knowledge of what was discussed in the previous three sessions.

Reference Ebook

Statistical Inference for Data Science by Brian Caffo